The present invention generally relates to a system and a method for generating a recommendation on a mobile device. More specifically, the present invention relates to a system and a method for generating a recommendation on a mobile device that may use a time, a location, a venue and/or an event to generate the recommendation. Further, the system and the method for generating a recommendation on a mobile device may use an event database to determine the current interests of the user. Still further, the system and the method for generating a recommendation on a mobile device may use a transactional history of the user and/or behavior of other users to generate the recommendation. The system and the method for generating a recommendation on a mobile device may recommend, for example, digital media, news and event information, editorial content and/or physical or digital merchandise. As a result, the system and the method for generating a recommendation on a mobile device may generate a recommendation that corresponds to the current interests of the user.
Mobile digital media is a rapidly growing segment of the entertainment industry made feasible by the prevalence of mobile devices operating on high-speed cellular and wireless networks. Consumers of media on mobile devices are faced with an increasing array of content to consume. Mobile devices are limited in screen space and user input functionality, and users are generally viewing content for short durations. Therefore, proactively directing users toward content that is of interest to them is paramount in making the mobile media experience a successful one.
The rise of e-commerce through online shopping destinations, such as Amazon.com (registered trademark of Amazon.com, Inc.), has generated tremendous interest in the area of item recommendation. Merchants that are able to deploy an accurate recommendation system, typically based on individual and aggregated user purchasing and other information, may greatly increase revenue.
The addition of Global Positioning System (hereinafter “GPS”) support to many mobile devices enables a large and growing number of applications that recommend and/or select content based on a location of a user. For example, hand-held and vehicle-based GPS systems may make restaurant recommendations according to the location of the user.
Most existing item recommendation systems do not consider both local time and location information of the user. Thus, the existing item recommendation systems miss important factors that may strongly influence a choice of which mobile media to consume. Conversely, existing location-based services that make recommendations, such as, for example, nearby restaurants, operate using simple selection and sorting criteria, and do not consider such factors as historical behavior of the user or the behavior of other users. Furthermore, no systems correlate local time and location information with a real world event to accurately determine a current environment of the user. For example, the same venue may be used one night for a sporting event and another night for a music performance. A location-based content recommendation system should consider the current environment of the user to avoid making inappropriate recommendations.
A need, therefore, exists for a system and a method for generating a recommendation on a mobile device. Further, a need exists for a system and a method for generating a recommendation on a mobile device that use a time, a location, a venue and/or an event to generate the recommendation. Still further, a need exists for a system and a method for generating a recommendation on a mobile device that use a transactional history of the user and/or behavior of other users to generate the recommendation. Moreover, a need exists for a system and a method for generating a recommendation on a mobile device that use an event database to generate the recommendation based on a specific event.